3.2.4. Spatial Optimization Based on Comparative Advantage

The theory of comparative advantage holds that there are differences in resource endowment between different regions that determine the different efficiency levels in the utilization of different commodities within those regions. Comparative advantage can be gained through exchange [78]. The standard Normalized Revealed Comparative Advantage index (NRCA), which is not constrained by time and space, can be used to evaluate the dominant function of each city, and determine the comparative advantage function of the city scientifically and effectively [79]. Therefore, under the guidance of PLES function theory, the spatial pattern of urban agglomeration can be optimized by constructing a normalized revealed comparative advantage index combined with system clustering and GIS technology. For example, taking the PLE function as a breakthrough point, Xu [79] introduced the NRCA based on the comparative advantage theory, determined the distribution pattern in the dominant functions of land space in the middle reaches of the Yangtze River urban agglomeration, and put forward a realization path for the optimal utilization of territorial space; Wei et al. [80] analyzed the land spatial characteristics of urban agglomerations in the upper reaches of the Yangtze River via the entropy weight method and function evaluation method from the perspective of the PLE function, and built a spatial-function comparative-advantage index to explore the optimization path of the land-space optimization scheme.

The optimization of PLES belongs to the research category working on the optimal allocation of land and resources, and the optimization of its quantitative structure and spatial layout is an important part of previous research [6]. From a theoretical perspective, the related theories of regional resources and environmental carrying capacity, urbanization, and ecological environment coupling play a major supporting role. From the perspective of research methods, the traditional technology for the optimal allocation of land resources is often used to construct economic models or landscape ecological models for optimizing the quantity ratio or land allocation in order to realize the optimization of land spatial patterns based on PLES. Research can, moreover, explore different scales, such as provinces, cities (urban agglomerations), counties, towns, and villages, covering different areas, such as cities and villages; and urban–rural ecotones, such as coastal zones, mining reclamation areas, and island fishing villages [81–84]. However, due to the lack of a unified technical system for the division of PLES at different scales and for different geographical types, along with the systematic combing and summarization of concepts for optimizing PLES patterns, the optimization of PLES requires further research.
